Questions about overlapping test and real-time prediction

[cccvision]

hi authors, I have some questions about the overlapping test, thanks in advance for your help!

1. Can this work really run in real-time? In the paper, it is written that ' AGRoL model achieves real-time inference speed' because it 'produces 196 output frames in 35 ms'. However, for online prediction, given one new observation, we only need one prediction (like what AvatarPoser did), 196 outputs seem redundant, how do you make it work for real-time usage?

2. when I tried to test with overlapping, It shows the following errors:
   python test.py --model_path /path/to/your/model --timestep_respacing ddim5 --support_dir /path/to/your/smpls/dmpls --dataset_path ./dataset/AMASS/ --overlapping_test

Loading dataset...
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 536/536 [00:00<00:00, 1072.94it/s]
Creating model and diffusion...
Loading checkpoints from [pretrained_weights/diffmlp.pt]...
Overlapping testing...
0%| | 0/536 [00:00<?, ?it/s]
Traceback (most recent call last):
File "test.py", line 552, in
main()
File "test.py", line 516, in main
output, body_param, head_motion, filename = test_func(
File "test.py", line 269, in overlapping_test
memory_end_index = sparse_splits[step_index][1]
IndexError: index 1 is out of bounds for dimension 0 with size 1

[asanakoy]

Hey. Even if you run prediction with a sliding window of stride 1, then it will require 35 ms per every prediction. Which is ~30 FPS